The collection and analysis of data are continuously growing due to the pervasiveness of
computing devices. The analysis of such information is fostering businesses and …

The number of mobile devices, such as smartphones and smartwatches, is relentlessly
increasing, to almost 6.8 billion by 2022, and along with it, the amount of personal and …

In recent years, privacy-preserving data mining has been studied extensively, because of
the wide proliferation of sensitive information on the internet. A number of algorithmic …

In the context of sharing video surveillance data, a significant threat to privacy is face
recognition software, which can automatically identify known people, such as from a …

We provide here an overview of the new and rapidly emerging research area of privacy
preserving data mining. We also propose a classification hierarchy that sets the basis for …

This paper explores the possibility of using multiplicative random projection matrices for
privacy preserving distributed data mining. It specifically considers the problem of computing …

Large repositories of data contain sensitive information that must be protected against
unauthorized access. The protection of the confidentiality of this information has been a long …

Publisher Summary Data mining services require accurate input data for their results to be
meaningful, but privacy concerns may influence users to provide spurious information. The …

One crucial aspect of privacy preserving frequent itemset mining is the fact that the mining
process deals with a trade-off: privacy and accuracy, which are typically contradictory, and …

Large repositories of data contain sensitive information which must be protected against
unauthorized access. Recent advances, in data mining and machine learning algorithms …